smids_10x_deit_tiny_sgd_0001_fold3
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3822
- Accuracy: 0.85
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.0766 | 1.0 | 750 | 1.0931 | 0.4283 |
0.9667 | 2.0 | 1500 | 1.0054 | 0.5083 |
0.9193 | 3.0 | 2250 | 0.9314 | 0.5533 |
0.7955 | 4.0 | 3000 | 0.8645 | 0.595 |
0.78 | 5.0 | 3750 | 0.7998 | 0.6283 |
0.6828 | 6.0 | 4500 | 0.7419 | 0.6833 |
0.6256 | 7.0 | 5250 | 0.6910 | 0.715 |
0.6533 | 8.0 | 6000 | 0.6501 | 0.7417 |
0.5725 | 9.0 | 6750 | 0.6153 | 0.76 |
0.5585 | 10.0 | 7500 | 0.5875 | 0.7733 |
0.5119 | 11.0 | 8250 | 0.5647 | 0.7917 |
0.4751 | 12.0 | 9000 | 0.5443 | 0.8033 |
0.4748 | 13.0 | 9750 | 0.5264 | 0.815 |
0.543 | 14.0 | 10500 | 0.5129 | 0.8167 |
0.4792 | 15.0 | 11250 | 0.4995 | 0.8233 |
0.4638 | 16.0 | 12000 | 0.4900 | 0.8267 |
0.4373 | 17.0 | 12750 | 0.4791 | 0.8267 |
0.4624 | 18.0 | 13500 | 0.4695 | 0.8333 |
0.4581 | 19.0 | 14250 | 0.4625 | 0.8317 |
0.4031 | 20.0 | 15000 | 0.4549 | 0.8283 |
0.3798 | 21.0 | 15750 | 0.4466 | 0.8367 |
0.4127 | 22.0 | 16500 | 0.4410 | 0.84 |
0.4351 | 23.0 | 17250 | 0.4350 | 0.8433 |
0.4464 | 24.0 | 18000 | 0.4308 | 0.835 |
0.4334 | 25.0 | 18750 | 0.4260 | 0.8333 |
0.4382 | 26.0 | 19500 | 0.4212 | 0.8367 |
0.3088 | 27.0 | 20250 | 0.4169 | 0.8367 |
0.3982 | 28.0 | 21000 | 0.4136 | 0.8367 |
0.4061 | 29.0 | 21750 | 0.4101 | 0.8367 |
0.4007 | 30.0 | 22500 | 0.4079 | 0.84 |
0.3333 | 31.0 | 23250 | 0.4046 | 0.8417 |
0.3804 | 32.0 | 24000 | 0.4012 | 0.84 |
0.4007 | 33.0 | 24750 | 0.3989 | 0.8417 |
0.4048 | 34.0 | 25500 | 0.3970 | 0.8417 |
0.3319 | 35.0 | 26250 | 0.3948 | 0.8433 |
0.3736 | 36.0 | 27000 | 0.3932 | 0.8467 |
0.3994 | 37.0 | 27750 | 0.3918 | 0.8483 |
0.3998 | 38.0 | 28500 | 0.3900 | 0.8483 |
0.3526 | 39.0 | 29250 | 0.3888 | 0.85 |
0.4438 | 40.0 | 30000 | 0.3872 | 0.8483 |
0.3369 | 41.0 | 30750 | 0.3860 | 0.8517 |
0.3716 | 42.0 | 31500 | 0.3855 | 0.8517 |
0.3661 | 43.0 | 32250 | 0.3844 | 0.8517 |
0.3454 | 44.0 | 33000 | 0.3840 | 0.8517 |
0.3872 | 45.0 | 33750 | 0.3835 | 0.8517 |
0.3238 | 46.0 | 34500 | 0.3830 | 0.8517 |
0.404 | 47.0 | 35250 | 0.3826 | 0.8517 |
0.3607 | 48.0 | 36000 | 0.3823 | 0.8517 |
0.3506 | 49.0 | 36750 | 0.3823 | 0.8517 |
0.3442 | 50.0 | 37500 | 0.3822 | 0.85 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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Base model
facebook/deit-tiny-patch16-224